AI agents use udemy_guncelle to create or update resources in Udemy MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Udemy MCP environment.
The tool updates/modifies course content on Udemy via browser automation. This is a Write operation as it modifies existing data. Severity is high because an AI agent could inadvertently modify course content at scale across published courses, potentially affecting enrolled students and instructor reputation.
From the tool's definition 'kurs icerigini gunceller' (updates course content) using Playwright browser automation
Attacks that exploit this kind of access
Playwright ile Udemy'de kurs icerigini gunceller. It is categorised as a Write tool in the Udemy MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Udemy MCP server in PolicyLayer and add a rule for udemy_guncelle: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Udemy MCP. Nothing to install.
udemy_guncelle is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the udemy_guncelle rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for udemy_guncelle. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
udemy_guncelle is provided by the Udemy MCP server (mustafayilmazart/kesif-udemy-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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